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Having explored the limits of the ‘top-down’ factor model approach, let's move on to a newer, ‘bottom-up’ approach to hedge fund replication. This approach is distinctly different because it replicates individual strategies first, before then constructing composite portfolios from these individual replications. Although more complex to execute, the bottom-up approach has quickly gained support among many academics and market participants. New York University's Professor F. Whitelaw states that ‘replicating individual strategies and then constructing composite portfolios from these individual replications, has several key advantages over replicating a composite index directly. These advantages include superior tracking, greater flexibility, and potentially improved performance characteristics.’1

Unless you randomly opened the book to this chapter, you no doubt realize the dilemma that providers of linear factor-based hedge fund replication face: these models work best on the hedge fund strategies for which investors need them least! Conversely, they break down in explaining the very strategies for which replication models are most needed.

Linear factor models – or related techniques that mimic past return time series and their statistical properties – have the most explanatory power for strategies in which the dominant explanatory factor is simple directional equity exposure.2 Furthermore, basing replication ...

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